Senior Ai/Ml Engineer, Machine Learning Operations

Summary

Join Onebrief, a rapidly growing startup revolutionizing military staff workflows, as our second Machine Learning Engineer focused on MLOps. You will play a critical role in establishing and refining our AI/ML deployment pipelines, leading MLOps initiatives to enhance operational efficiencies and ensure scalability and reliability. You will design and implement scalable systems for model deployment, monitoring, and maintenance, working closely with cross-functional teams. Your expertise will directly impact the deployment and performance of AI models optimizing military operational planning. This role requires a strong background in applied Machine Learning and AI, experience building scalable systems, and proficiency in various technologies. Onebrief offers the opportunity to be a pioneering MLOps engineer in a dynamic startup environment.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field
• 4+ years in engineering roles with significant MLOps contributions
• Strong programming skills in Python
• Hands-on experience with container orchestration tools like Docker and Kubernetes
• Proficient in designing and deploying agentic systems with modern model serving frameworks (e.g., LangChain, vLLM, FastAPI, or KServe)
• Experience with systems architecture, SQL/NoSQL databases, and Git version control
• Strong proficiency with CI/CD pipelines and distributed computing frameworks like Ray or Dask
• Familiarity with model monitoring, logging, and versioning tools (e.g., MLflow, Weights & Biases)
• Proven expertise in deploying machine learning models in cloud environments (AWS, Azure, or GCP)

Responsibilities

• Establish and refine AI/ML deployment pipelines
• Lead MLOps initiatives
• Enhance operational efficiencies
• Ensure scalability and reliability in delivering machine learning solutions to production
• Design and implement scalable systems for model deployment, monitoring, and maintenance
• Ensure that our AI solutions are robust, efficient, and seamlessly integrated into our platform
• Build a reliable ML infrastructure that supports rapid growth and innovation

Preferred Qualifications

• Master's or Ph.D. is a plus
• Knowledge of advanced decision theory
• Experience with API building, simulation environments, and reinforcement learning pipelines
• Proficiency with inference runtimes/servers like ONNX, Triton, or similar technologies
• Design thinking approach to problem-solving and iterative development
• Strong problem-solving abilities with a bias towards action
• Excellent communication and collaboration skills
• Ability to work autonomously in a fast-paced, dynamic environment